1
Digitalizing Infectious Disease Clinical Guidelines
for Improved Clinician Satisfaction
Session #64, February 12, 2019
Stephanie H. Hoelscher MSN, RN-BC, CPHIMS, CHISP
Chief Clinical Analyst, Texas Tech University Health Sciences Center
2
Stephanie H. Hoelscher MSN, RN-BC, CPHIMS, CHISP
Has no real or apparent conflicts of interest to report.
Conflict of Interest
3
Agenda
Objectives
Background
Design & Methods
Data Analysis
Next Steps
Conclusion
4
Learning Objectives
Define
Define the
process for
development
and build of a
new CDS
workflow
List
List the pros and
cons of a CDS
system within an
electronic health
record regarding
the demonstrated
enhanced process
Identify
Identify methods
used to include
clinicians in the CDS
development and
validation process
for an enhanced
infectious disease
process
5
Emerging Infectious Diseases
Rapid Deployment Model
Ebola, Zika, Virus X?
Quadruple Aim
21
st
Century Cures Act
Decreasing documentation burden
Digitalizing Clinical Guidelines
CDC Kaizen 2018
Ongoing Workgroups
Background
West
Nile
MERS
TB
Zika
Polio
Virus
X
Measles
Ebola
6
* The project’s goal was to balance aspects of the
quadruple aim, including enhancing the patient
experience and improving clinician EHR
satisfaction by 5% by December 2018.
GOALS
7
Current/Future State Workflow Assessments
Evidence Review
Integration of travel timeframe
Updates of current CDC/ISID travel hotspots
Updates of symptomology
Integration of exposure reporting and vaccine status
Enhanced Functionality
Event set hierarchy changes
Change to HTML Alert format
Nursing intake documentations modifications
What Did We Do?
8
Design & Methods
Plan-Do-Study-Act
Focus Groups
Current/Future State Workflows
Pre & Post Surveys
9
Plan-Do-Study-Act
The PDSA structure of rapid
cycle deployment with the
Model for Improvement
Supports strategies for
shortening design,
implementation and
evaluation cycles
(Langley et al., 2009)
10
Clinician Focus Groups
NIC/ANICS
ID Providers
Governance
NIC and ANIC Committees
Infectious Disease CDS
Rules & Alerts Committee
Use & Standards
What Did We Do?
11
ALGORITHMS
12
Existing:
Ebola
Zika
New:
Yellow Fever
Measles
Tuberculosis (TB)
Generic Travel Alert
Later, by request:
MERS (for the Hajj, seasonal)
West
Nile
MERS
TB
Zika
Polio
Virus
X
Measles
Ebola
13
Nursing Intake Enhancements
(Cerner Images Approved, 2018)
14
Design HTML Alerts
Evoke
Inpatient versus Outpatient
Provider versus Non-Provider
Open Chart
Functionality
Message to Infection Control
Communication of alert
Orders links
Evidence-based guidelines
CDC
IDSA
(Cerner Image Approved, 2018)
15
Survey Clinician Satisfaction
Pre and Post-implementation (open 45 days each)
Qualtrics
Anonymous, voluntary
Randomized eGift card drawing to voluntary email submissions
$10 X 50 eGift cards
Quality Improvement Review Board (QIRBs) approval and
Institutional Review Board (IRB) exemption was determined
Pre & Post Implementation Surveys
16
2280/2277 Recipients
Staff (nursing assistants/medical assistants)
Nurses (registered nurses/licensed vocational nurses)
APPs, residents, fellows, PharmD, and faculty
Responses
Pre: n = 465 (20.4%)
Post: n = 394 (17.3%)
Pre & Post-Implementation Surveys
17
Demographics
CISIES 2.0 (Clinical Information Systems Implementation Evaluation Scale)
34-question six-point Likert scale
Ranges from Strongly Disagree to Strongly Agree
CISIES 2.0 is an updated version of the 2006-2011
CISIES 1.0 and 1.1
Qualitative Textual Questions
Pre & Post Implementation Surveys
18
* Note: there was minimal incidence of “straight-lining” issues
Data Analysis CISIES 2.0
Interpretive guide
Score range from
Below -0.5 (clear dissatisfaction), to 4 to 5 (very high degree of satisfaction)
(Gugerty & Carlson, 2016)
19
Demographics
Variable
Category
n %
Gender
Male
55 18
Female
246 82
Age
18
-25 22 7.1
26
-30 40 12.9
31
-40 75 24.3
41
-50 65 21
51
-60 73 23.6
61+
34 11
Professional
CMA/Nurse Aide
27 8.7
Role
RN
159 51.5
LVN
52 16.8
Advanced Practice Provider
9 2.9
PharmD
1 0.3
Resident/Fellow
21 6.8
Faculty
38 12.3
Other
2 0.6
Computer
Novice
8 2.6
Experience
Competent
51 16.5
Proficient
179 57.9
Expert
71 23
20
Did We Make a Difference?
21
Somewhat Satisfied
39%
Very Satisfied
3%
Moderately to Highly Satisfied
41%
Neutral
11%
Very Dissatisfied
6%
Pre-
Implementation
CISIES
Total
Score
22
Somewhat Satisfied
37%
Very Satisfied
9%
Moderately to Highly Satisfied
41%
Neutral
8%
Very Dissatisfied
5%
Post-
Implementation
CISIES
Total
Score
23
CISIES 2.0 Independent t-test
(IBM SPSS Statistics, Version 25.0, 2017)
24
Mann-Whitney U
CISIES Overall
(IBM SPSS Statistics, Version 25.0, 2017)
25
What were the
clinicians thoughts?
Textual Responses
How useful have you
found the infectious
disease model in the
electronic health record
to your clinical practice?
Is there anything else you
would like to tell us about
the infectious disease
design to improve
functionality within your
clinical workflow?
26
Textual Responses Negative
“It is difficult to obtain the information when the
patient is nonverbal and no family present”
“Not helpful and confusing to patients”
“I think it will be very misleading. You need to trust
human contact and human thinking”
“It will not help in any way in my practice”
“Presently EMR consumes far too much time in the
workday as it is. Adding more is met with suspicion”
CISIES
27
Textual Responses Positive
“Very helpful, the one used now is not as expanded as
we need it to be”
“Will improve monitoring and reporting of infectious
disease concerns”
“Will update the information on my patient instantly to
improve outcome of patient care”
“VERY-I work in the EC and when we have an infectious
disease case it can sometimes be chaotic”
“It has been very helpful with the students who study
abroad”
CISIES
28
Yes and no…
Almost all scores higher on the post-survey (improvement)
Not all were statistically significant
Preliminary data suggests RNs were much more impressed
with the changes than MDs
Profoundly difficult workflow to improve upon
It is an EHR/Alert fatigue
Emerging infectious diseases are moving targets
Change perceived as more work, even when it isn’t
Created a complex process that might be difficult to maintain
Did We Make a Difference?
29
Education and re-education
Nursing (in small pockets) had issues with understanding
the functionality of the new form
Adding the option of NA to new data fields (DTAs)
Had to be done
Gave too easy a way out
Initially, Pediatrics had poor responses
Did not perceive benefit to their population
Survey is more geared towards large scale system
implementation as opposed to small custom functionality
Limitations & Overall Issues
30
PDSA Cycle Work
Amended number of “firings” per encounter
Stop after 48 hours inpatient
Maintenance options for “US Areas at Risk”
Lack of proper usage
Removal of certain automated orders
i.e., isolation cart
$$$
Tightened rules regarding locations and symptomology
Limitations & Overall Issues
31
Maintenance, maintenance, maintenance
New emerging infectious diseases (not just travel related!)
Intermittent re-education (end-users AND informaticists)
Keep subject matter experts engaged
Continue work with CDC and support the ONC initiatives
New clinical decision support functionality on the horizon
Easing documentation burden for both providers AND nursing
Policy development
Continued testing of usability
Next Steps
32
Keep pushing because it can work
Keep those stakeholders involved
They often start out strong and then dwindle
Maintenance
Keep it evidence-based, safe, and simple
Keep an eye on what is coming
CDC/ONC initiatives
Talk to your vendor
Is yours ready?
Conclusion
33
Stephanie H. Hoelscher MSN RN-BC CPHIMS CHISP
Email: steph.hoelscher@ttuhsc.edu
Twitter: @StephHoelscher
Questions
Do not forget to complete the online session evaluation, thanks!
34
Dr. Fatma Levent (TTUHSC SOM)
Dr. Susan McBride (TTUHSC SON)
Maria Michaels (CDC)
Dr. Floyd Eisenberg
This project was made possible through a cooperative
agreement between the American Association of Colleges of
Nursing (AACN) and the Centers for Disease Control and
Prevention (CDC), award number NU36OE000009-02-02; its
contents are the responsibility of the authors and do not
necessarily reflect the official views of AACN or CDC.
Special Thanks…
35
GIC Informatics. (2015). CISIES 2.0. Retrieved from
http://www.gicinformatics.com/cisies
Gugerty, B., & Carlson, N. (2016). CISIES 2.0: Administration,
scoring, and interpretation guidelines. Retrieved from
gicinformatics.com/cisies
IBM Corp. Released 2017. IBM SPSS Statistics for Windows,
Version 25.0. Armonk, NY: IBM Corp.
Langley, G. J., Moen, R. D., Nolan, K. M., Nolan, T. W.,
Norman, C. L., & Provost, L. P. (2009). The Improvement
Guide (2
nd
ed.). San Francisco, CA: Jossey-Bass.
References